siggraph

Hydrographic Printing is a technique of transferring colored inks on a film to the surface of an object. The film is placed on water and activated with a chemical that allows it to adhere to an object being physically pushed onto it. Researchers at Zhejiang University and Columbia University have taken hydrographic printing to the next level (pdf link). In a technical paper to be presented at ACM SIGGRAPH 2015 in August, they explain how they developed a computational method to create complex patterns that are precisely aligned to the object.

Typically, repetitive patterns are used because the object stretches the adhesive film; anything complex would distort during this subjective process. It’s commonly used to decorate car parts, especially rims and grills. If you’ve ever seen a carbon-fiber pattern without the actual fiber, it’s probably been applied with hydrographic printing.

The physical setup for this hack is fairly simple: a vat of water, a linear motor attached to a gripper, and a Kinect. The object is attached to the gripper. The Kinect measures its location and orientation. This data is applied to a 3D-scan of the object along with the desired texture map to be printed onto it. A program creates a virtual simulation of the printing process, outputting a specific pattern onto the film that accounts for the warping inherent to the process. The pattern is then printed onto the film using an ordinary inkjet printer.

The tiger mask is our personal favorite, along with the leopard cat. They illustrate just how complex the surface patterns can get using single or multiple immersions, respectively. This system also accounts for objects of a variety of shapes and sizes, though the researchers admit there is a physical limit to how concave the parts of an object can be. Colors will fade or the film will split if stretched too thin. Texture mapping can now be physically realized in a simple yet effective way, with amazing results.

As 3D printing continues to grow, people are developing more and more ways to get 3D models. From the hardware based scanners like the Microsoft Kinect to software based like 123D Catch there are a lot of ways to create a 3D model from a series of images. But what if you could make a 3D model out of a single image? Sound crazy? Maybe not. A team of researchers have created 3-Sweep, an interactive technique for turning objects in 2D images into 3D models that can be manipulated.

To be clear, the recognition of 3D components within a single image is a bit out of reach for computer algorithms alone. But by combining the cognitive abilities of a person with the computational accuracy of a computer they have been able to create a very simple tool for extracting 3D models. This is done by outlining the shape similar to how one might model in a CAD package — once the outline is complete, the algorithm takes over and creates a model.

The software was debuted at Siggraph Asia 2013 and has caused quite a stir on the internet. Watch the fascinating video that demonstrates the software process after the break!

With high-speed cameras you’re able to see bullets passing through objects, explosions in process, and other high-speed phenomena. Rarely, though, are you able to see what happens when light shines on an object without hundreds of thousands of dollars worth of equipment. A group of researchers at The University of British Columbia are doing just that with hardware that is well within the range of any home tinkerer.

Making videos of light passing through and around objects has been done before (great animated gifs of that here), but the equipment required of previous similar projects cost $300,000 and couldn’t be used outside the controlled environment of a lab. [Matthias] and his team put together a similar system for about $1,000. The only hardware required is an off-the-shelf 3D time of flight camera and a custom driver powering six red laser diodes.

Aside from having a much less expensive setup than the previous experiments in recording the flight of a pulse of light, [Matthias] and his team are also able to take their and record the flight of light in non-labratory settings. They’ll be doing just that at this year’s SIGGRAPH conference, producing videos of light reflecting off attendee-produced objects in just a few minutes. You can check out the video for the project below.

Fresh from this year’s SIGGRAPH is a very interesting take on the traditional X Y-table based CNC machine from [Alec], [Ilan] and [Frédo] at MIT. They created a computer-controlled CNC router that is theoretically unlimited in size. Instead of a gantry, this router uses a human to move the tool over the work piece and only makes fine corrections to the tool path with the help of a camera and stepper motor.

The entire device is built around a hand held router, with a base that contains a camera, electronics, stepper motors, and a very nice screen for displaying the current tool path. After a few strips of QR code-inspired tape, the camera looks down at the work piece and calculates the small changes the router has to make in order to make the correct shape. All the user needs to do is guide the router along the outline of the part to be cut with a margin of error of a half inch.

You can read the SIGGRAPH paper here (or get the PDF here and not melt [Alec]’s server), or check out the demo video after the break.

[Vitor] et al came up with two versions of hardware for this project. The first is a dual stack of high-resolution LCD displays, while the second revision is an LCD with a lenticular overlay. With this hardware, the team can change the focal plane of an entire image, or just subsets of an image allowing for customized vision correction for anyone with nearsightedness, farsightedness, astigmatism, presbyopia, and even cataracts.

With plenty of head-mounted augmented reality platforms coming down the pipe such as Google’s Project Glass and a few retina displays, we could see this type of software-defined vision correction being very useful for the 75% of adults who use some form of vision correction. It may just be a small step towards the creation of a real-life VISOR, but we glasses-wearing folk will take what we can get.

You can check out the .PDF of the paper here, or watch the video after the break.

[Gil] sent in an awesome paper from this year’s SIGGRAPH. It’s a way to detect subtle changes in a video feed from [Hao-Yu Wu, et al.] at the MIT CS and AI lab and Quanta Research. To get a feel for what this paper is about, check out the video and come back when you pick your jaw off the floor.

The project works by detecting and amplifying very small changes in color occurring in several frames of video. From the demo, the researchers were able to detect someone’s pulse by noting the very minute changes in the color of their skin whenever their face is pumped full of blood.

A neat side effect of detecting small changes in color is the ability to also detect motion. In the video, there’s an example of detecting someone’s pulse by exaggerating the expanding artery in someone’s wrist, and the change in a shadow produced by the sun over the course of 15 seconds. This is Batman-level tech here, and we can’t wait to see an OpenCV library for this.

Even though the researchers have shown an extremely limited use case – just pulses and breathing – we’re seeing a whole lot of potential applications. We’d love to see an open source version of this tech turned into a lie detector for the upcoming US presidential debates, and the motion exaggeration is perfect for showing why every sports referee is blind as a bat.

If you want to read the actual paper, here’s the PDF. As always, video after the break.

We know it’s shopped, but we can’t tell because of the pixels. PhD student [Kevin Karsch] along with a few other friends will be presenting their methods to render objects into preexisting photos at SIGGRAPH Asia next month.

The paper (PDF…) covers how [Kevin] et al. go about putting impossible objects into photos. The user first defines the geometry of the picture; legs of tables are defined and the table top is extruded from these legs. The lights are then defined by drawing a bounding box and with a little bit of algorithmic trickery, a 3D object is inserted into the scene.

Comparing the results to the original picture is jaw-dropping. For us, photoshopping a bunch of billiard balls on a pool table would take hours, and it would never look quite right. [Kevin]’s work for SIGGRAPH can do the whole scene in minutes and produces results we couldn’t dream of.

There’s no downloadable software yet, but the algorithms are there. Check out the video demo of the techniques and results after the break.